I’m a fourth-year PhD researcher in TU Delft’s Department of Transport & Planning, specialising in applied machine learning for urban transportation and city logistics.

I develop probabilistic forecasting and reinforcement learning methods to support decisions in shared mobility, multimodal travel and last-mile delivery. My work combines transformer and graph-based learning with an understanding of transport networks, fleet operations and uncertainty in real-world demand and supply.

Within the European SUM project, I led modelling and coordinated delivery of a shared-mobility forecasting service integrated into RET’s live travel-planning app in Rotterdam. My work with industry partners spans data access, model integration, app functionality and user evaluation. Earlier research with Takeaway.com connected demand forecasting with courier management and delivery operations.

I hold an MSc in Computational Science from the University of Amsterdam and a BSc in Econometrics and Operations Research from Erasmus University Rotterdam.

Explore my work · View my CV

I’m interested in industry opportunities in applied research, machine learning, data science and technical innovation, with a particular interest in mobility, transport and logistics, and other settings where predictive models inform operational decisions.

For opportunities or research collaborations, send me an email or connect on LinkedIn.